61 citations · 83 across the 12 of their papers we have counts for
5 papers · 1 filter
Federated Social Recommendation with Graph Neural Network
Zhiwei Liu, Liangwei Yang, Ziwei Fan +2
Recommender systems have become prosperous nowadays, designed to predict users' potential interests in items by learning embeddings. Recent developments of the Graph Neural Network…
DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN
Yu Wang, Zhiwei Liu, Ziwei Fan +2
In the information explosion era, recommender systems (RSs) are widely studied and applied to discover user-preferred information. A RS performs poorly when suffering from the cold…
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Ziwei Fan, Zhiwei Liu, Jiawei Zhang +3
In order to model the evolution of user preference, we should learn user/item embeddings based on time-ordered item purchasing sequences, which is defined as Sequential Recommendat…
Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation
Ziwei Fan, Zhiwei Liu, Lei Zheng +2
The sequential patterns within the user interactions are pivotal for representing the user's preference and capturing latent relationships among items. The recent advancements of s…
Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer
Zhiwei Liu, Ziwei Fan, Yu Wang +1
Sequential Recommendation characterizes the evolving patterns by modeling item sequences chronologically. The essential target of it is to capture the item transition correlations.…